Factors influencing healthcare provider respondent fatigue answering a globally administered in-app survey
Factors influencing healthcare provider respondent fatigue answering a globally administered in-app survey
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DOI：
10.7717/peerj.3785
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发表时间：
2017-09-12
期刊：
影响因子：
2.7
通讯作者：
O'Reilly-Shah, Vikas N.
中科院分区：
文献类型：
--
作者：
O'Reilly-Shah, Vikas N.
背景被访者疲劳，又称调查疲劳，是调查数据收集中常见的问题。已知影响受访者疲劳的因素包括调查长度，调查主题，问题复杂性和开放式问题类型。由于从这些从业者那里获得的信息的价值，人们对了解医生调查响应性的驱动因素有很大的兴趣。随着最近移动的智能电话技术的爆炸式增长，已经可以在逐个问题的基础上从移动的应用（app）的用户获得调查数据。作者获得了基本的人口统计学调查数据以及与sugammadex麻醉药相关的调查数据，并利用无应答率来检查影响应答者疲劳的因素。主要数据收集于2015年12月至2017年2月之间。从移动的麻醉计算器应用程序的全球用户中收集调查和应用程序内分析。关键自变量为用户国家、医疗保健提供者角色、应用程序对个人实践的重要性评级、实践时间长度和应用程序使用频率。关键因变量是应答者疲劳的度量。提供商角色和世界银行国家收入水平预测了这项应用内调查的受访者疲劳率。应用程序对提供者的重要性和实践时间长度与疲劳适度相关。应用程序使用频率不相关。这项研究的重点是一个主题与应用程序的主题领域密切相关的调查。如果主题不密切相关，受访者的疲劳率可能会发生巨大变化。讨论。虽然应用程序可以作为强大的数据收集平台，但应用程序内调查的回复率可能会因重要的受访者特征而有所不同。研究应精心设计，以减轻疲劳，以及与可能有较高的应答疲劳率的应答者的特征的理解供电。
Background. Respondent fatigue, also known as survey fatigue, is a common problem in the collection of survey data. Factors that are known to influence respondent fatigue include survey length, survey topic, question complexity, and open-ended question type. There is a great deal of interest in understanding the drivers of physician survey responsiveness due to the value of information received from these practitioners. With the recent explosion of mobile smartphone technology, it has been possible to obtain survey data from users of mobile applications (apps) on a question-by-question basis. The author obtained basic demographic survey data as well as survey data related to an anesthesiology-specific drug called sugammadex and leveraged nonresponse rates to examine factors that influenced respondent fatigue.Methods. Primary data were collected between December 2015 and February 2017. Surveys and in-app analytics were collected from global users of a mobile anesthesia calculator app. Key independent variables were user country, healthcare provider role, rating of importance of the app to personal practice, length of time in practice, and frequency of app use. Key dependent variable was the metric of respondent fatigue.Results. Provider role and World Bank country income level were predictive of the rate of respondent fatigue for this in-app survey. Importance of the app to the provider and length of time in practice were moderately associated with fatigue. Frequency of app use was not associated. This study focused on a survey with a topic closely related to the subject area of the app. Respondent fatigue rates will likely change dramatically if the topic does not align closely.Discussion. Although apps may serve as powerful platforms for data collection, responses rates to in-app surveys may differ on the basis of important respondent characteristics. Studies should be carefully designed to mitigate fatigue as well as powered with the understanding of the respondent characteristics that may have higher rates of respondent fatigue.